This invention relates to image analysis apparatus, particularly for collision warning and and avoidance systems.
The cost of road traffic accidents, both in terms of economics and human misery is vast. For example, in 1999 the US Federal Highway Administration reported 6.3M Road Traffic Accidents (RTA) in the USA which left 3.2M people injured and 41,345 dead. The total economic cost was estimated to be $150 Bn.
Similarly, the Economic Commission for Europe reported that in 1997, European RTA injured 6,118,844 people and killed 164,677. The direct costs of Medical treatment, emergency services, damage to property & lost economic output were estimated to be £36 Bn, whilst the total economic cost to the EEC was estimated at £150 Bn.
Therefore, much research has focussed on finding ways to avoid collisions and RTA by the provision of better driver information and the active and early warning of danger and this has lead to a variety of approaches.
The simplest collision avoidance solutions rely on measuring the distance from the vehicle to the nearest vehicle in front and providing a warning light or sound to the driver if he is driving too close, given his current speed.
One simple approach to measuring distance is to use a laser rangefinder (LRF). These devices work on the basis of measuring the time of flight of a laser pulse to a remote object and back and calculating the distance from the known velocity of light. A limitation of such devices is that they are only able to monitor the distance over a predefined zone directly in front on the vehicle as shown in FIG. 1(A). The path of the vehicle 1 is shown as 2, and the distance monitoring zone is shown as 4. If the vehicle is travelling round a bend, the region being monitored will not be focussed on the vehicle's path, but will look either into the path of oncoming traffic or into the kerbside as illustrated in FIG. 1, situations (B) and (C.).
This is leads to false collision earnings when the road curves or the driver turns which substantially reduces the benefit of such systems and hence their attractiveness to the motorist or commercial driver. In addition, these false warnings make the use of such systems to automatically control vehicle braking, which would otherwise improve vehicle reaction time to dangerous circumstances, problematic.
Nonetheless, simple LRF based approaches can provide a cost effective solution for collision warning or intelligent cruise control systems (where the car velocity is automatically controlled to maintain a safe distance behind the car in front) for motorway driving.
To overcome the problem of false warnings on everyday roads and encourage more widespread adoption of collision warning, many alternative approaches have been tried.
For example, systems have been developed (such as the Eaton® VORAD® system) which use forward looking doppler microwave radar techniques to measure the distance to a number of local vehicles. Unfortunately such systems are expensive to produce because of the sophisticated nature of their components and technology and as a result their application has been limited to the commercial vehicle market where a higher system price can be tolerated because the vehicles are themselves more expensive and the economic cost of a collision is higher.
Other workers have adopted the approach of scanning the laser rangefinder over the scene in front of a vehicle to measure the distance to other vehicles or obstacles. The scanning is usually accomplished with a rotating mirror. However, the mirror needs to be big enough to encompass the laser beam and aperture of the LRF's receiving optics without causing crosstalk or vignetting of the image. This adds cost and mechanical complexity.
To realise a lower cost system other workers have been attempting to use a “sensor fusion” approach, whereby distance data gathered by a LRF or radar is combined with information captured by a video camera and image processing system to try to eliminate false readings. Such systems often use a priori knowledge about the likely size and shape of vehicles and cues from road markings and road furniture to evaluate where the lanes and edges of the road are to check whether the LRF distance data is usable and valid. In addition, some systems modify the video cameras image data to draw the driver's attention to potential threats in the field of view.
However, the road environment is very unstructured from an image processing point of view. This presents a difficult image processing problem requiring substantial and expensive computing resources to extract reliable data. Even with such resources, these systems find it very difficult to cope with unexpected features in the image; for example a child running into the path of the vehicle or some other obstruction in the road, because of their reliance on a priori knowledge. As a result, the high cost of the necessary computing resources and the problem of false warnings has delayed the commercialisation of such systems.
As a further alternative to using laser rangefinding or radar techniques to measure distance to objects over a field of view in front of a vehicle systems using two video cameras and stereographic image processing techniques have been deployed (e.g. JP2001/01873S). However, the baseline of such systems is limited by the size of the vehicle and this compromises range accuracy. In addition, the problems identified above with regard to image processing also apply.